Papers
15
Total Citations
260
H-Index
6
About
Mohammad Shahbazi is a leading researcher in the field of legged robotics, with a primary focus on energy-efficient locomotion, dynamic gait transitions, and bio-inspired control systems. His most significant contributions center on the application and extension of the spring-loaded inverted pendulum (SLIP) model, a foundational template for understanding and generating running and walking behaviors. Shahbazi’s work is distinguished by its theoretical depth, providing unified modeling and control frameworks that enable seamless transitions between walking and running—a critical challenge in humanoid robotics. His 2018 overview on energy-efficient robot locomotion, with 116 citations, systematically highlights the efficiency gap between biological and robotic systems, setting a benchmark for the field. He has also developed innovative analytical approximations for the complex double-stance phase of walking, as well as neural-network-controlled templates for humanoid running. Beyond terrestrial locomotion, his research extends to marine robotics, visual-inertial tracking, and postural balance control. With over 240 total citations, Shahbazi’s work is essential reading for students and researchers aiming to bridge the gap between biological agility and robotic performance.
Research Focus
Key Achievements
Top Papers
- 1An Overview on Principles for Energy Efficient Robot Locomotion116 citations · 2018
- 2
- 3Automated Transitions Between Walking and Running in Legged Robots13 citations · 2014
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- 5Analytical approximation for the double-stance phase of a walking robot10 citations · 2015
- 6Neural-Network-Controlled Spring Mass Template for Humanoid Running8 citations · 2018
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- 9Observer-based postural balance control for humanoid robots5 citations · 2013
- 10